Modification of Gesture-Determined-Dynamic Function with Consideration of Margins for Motion Planning of Humanoid Robots

The gesture-determined-dynamic function (GDDF) offers an effective way to handle the control problems of humanoid robots. Specifically, GDDF is utilized to constrain the movements of dual arms of humanoid robots and steer specific gestures to conduct demanding tasks under certain conditions. However, there is still a deficiency in this scheme. Through experiments, we found that the joints of the dual arms, which can be regarded as the redundant manipulators, could exceed their limits slightly at the joint angle level. The performance straightly depends on the parameters designed beforehand for the GDDF, which causes a lack of adaptability to the practical applications of this method. In this paper, a modified scheme of GDDF with consideration of margins (MGDDF) is proposed. This MGDDF scheme is based on quadratic programming (QP) framework, which is widely applied to solving the redundancy resolution problems of robot arms. Moreover, three margins are introduced in the proposed MGDDF scheme to avoid joint limits. With consideration of these margins, the joints of manipulators of the humanoid robots will not exceed their limits, and the potential damages which might be caused by exceeding limits will be completely avoided. Computer simulations conducted on MATLAB further verify the feasibility and superiority of the proposed MGDDF scheme

Neural-Dynamic Based Synchronous-Optimization Scheme of Dual Redundant Robot Manipulators

In order to track complex-path tasks in three dimensional space without joint-drifts, a neural-dynamic based synchronous-optimization (NDSO) scheme of dual redundant robot manipulators is proposed and developed. To do so, an acceleration-level repetitive motion planning optimization criterion is derived by the neural-dynamic method twice. Position and velocity feedbacks are taken into account to decrease the errors. Considering the joint-angle, joint-velocity, and joint-acceleration limits, the redundancy resolution problem of the left and right arms are formulated as two quadratic programming problems subject to equality constraints and three bound constraints. The two quadratic programming schemes of the left and right arms are then integrated into a standard quadratic programming problem constrained by an equality constraint and a bound constraint. As a real-time solver, a linear variational inequalities-based primal-dual neural network (LVI-PDNN) is used to solve the quadratic programming problem. Finally, the simulation section contains experiments of the execution of three complex tasks including a couple task, the comparison with pseudo-inverse method and robustness verification. Simulation results verify the efficacy and accuracy of the proposed NDSO scheme

Model-based recurrent neural network for redundancy resolution of manipulator with remote centre of motion constraints

Redundancy resolution is a critical issue to achieve accurate kinematic control for manipulators. End-effectors of manipulators can track desired paths well with suitable resolved joint variables. In some manipulation applications such as selecting insertion paths to thrill through a set of points, it requires the distal link of a manipulator to translate along such fixed point and then perform manipulation tasks. The point is known as remote centre of motion (RCM) to constrain motion planning and kinematic control of manipulators. Together with its end-effector finishing path tracking tasks, the redundancy resolution of a manipulators has to maintain RCM to produce reliable resolved joint angles. However, current existing redundancy resolution schemes on manipulators based on recurrent neural networks (RNNs) mainly are focusing on unrestricted motion without RCM constraints considered. In this paper, an RNN-based approach is proposed to solve the redundancy resolution issue with RCM constraints, developing a new general dynamic optimisation formulation containing the RCM constraints. Theoretical analysis shows the theoretical derivation and convergence of the proposed RNN for redundancy resolution of manipulators with RCM constraints. Simulation results further demonstrate the efficiency of the proposed method in end-effector path tracking control under RCM constraints based on an industrial redundant manipulator system

A recurrent neural network applied to optimal motion control of mobile robots with physical constraints

Conventional solutions, such as the conventional recurrent neural network (CRNN) and gradient recurrent neural network (GRNN), for the motion control of mobile robots in the unified framework of recurrent neural network (RNN) are difficult to simultaneously consider both criteria optimization and physical constraints. The limitation of the RNN solution may lead to the damage of mobile robots for exceeding physical constraints during the task execution. To overcome this limitation, this paper proposes a novel inequality and equality constrained optimization RNN (IECORNN) to handle the motion control of mobile robots. Firstly, the real-time motion control problem with both criteria optimization and physical constraints is skillfully converted to a real-time equality system by leveraging the Lagrange multiplier rule. Then, the detailed design process for the proposed IECORNN is presented together with the neural network architecture developed. Afterward, theoretical analyses on the motion control problem conversion equivalence, global stability, and exponential convergence property are rigorously provided. Finally, two numerical simulation verifications and extensive comparisons with other existing RNNs, e.g., the CRNN and the GRNN, based on the mobile robot for two different path-tracking applications sufficiently demonstrate the effectiveness and superiority of the proposed IECORNN for the real-time motion control of mobile robots with both criteria optimization and physical constraints. This work makes progresses in both theory as well as practice, and fills the vacancy in the unified framework of RNN in motion control of mobile robots

Motion planning by demonstration with human-likeness evaluation for dual-arm robots

© 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThe paper presents a planning procedure that allows an anthropomorphic dual-arm robotic system to perform a manipulation task in a natural human-like way by using demonstrated human movements. The key idea of the proposal is to convert the demonstrated trajectories into attractive potential fields defined over the configuration space and then use an RRT*-based planning algorithm that minimizes a path-cost function designed to bias the tree growth towards the human-demonstrated configurations. The paper presents a description of the proposed approach as well as results from a conceptual and a real application example, the latter using a real anthropomorphic dual-arm robotic system. A path-quality measure, based on first-order synergies (correlations between joint velocities) obtained from real human movements, is also proposed and used for evaluation and comparison purposes. The obtained results show that the paths obtained with the proposed procedure are more human-like.Peer ReviewedPostprint (author's final draft

Human-In-The-Loop Control and Task Learning for Pneumatically Actuated Muscle Based Robots

Pneumatically actuated muscles (PAMs) provide a low cost, lightweight, and high power-to-weight ratio solution for many robotic applications. In addition, the antagonist pair configuration for robotic arms make it open to biologically inspired control approaches. In spite of these advantages, they have not been widely adopted in human-in-the-loop control and learning applications. In this study, we propose a biologically inspired multimodal human-in-the-loop control system for driving a one degree-of-freedom robot, and realize the task of hammering a nail into a wood block under human control. We analyze the human sensorimotor learning in this system through a set of experiments, and show that effective autonomous hammering skill can be readily obtained through the developed human-robot interface. The results indicate that a human-in-the-loop learning setup with anthropomorphically valid multi-modal human-robot interface leads to fast learning, thus can be used to effectively derive autonomous robot skills for ballistic motor tasks that require modulation of impedance

Nyku: A Social Robot for Children With Autism Spectrum Disorders

The continued growth of Autism Spectrum Disorders (ASD) around the world has spurred a growth in new therapeutic methods to increase the positive outcomes of an ASD diagnosis. It has been agreed that the early detection and intervention of ASD disorders leads to greatly increased positive outcomes for individuals living with the disorders. Among these new therapeutic methods, Robot-Assisted Therapy (RAT) has become a hot area of study. Recent works have shown that high functioning ASD children have an affinity for interacting with robots versus humans. It is proposed that this is due to a less complex set of communication modes present in a robotic system as opposed to the complex non-verbal communications present in human to human interactions. As such, the Computer Vision and Robotics Lab at the University of Denver has embarked on developing a social robot for children with ASD. This thesis presents the design of this social robot; Nyku (Figure 1). It begins with an investigation of what the needs of ASD children are, what existing therapies help with, and what, if any, roles a robot can play in these treatment plans. From the literature examined, it is clear that robots designed specifically for ASD children have a core set of goals, despite the varied nature of the disorder\u27s spectrum. These goals aim to reduce the stress of non-verbal communications that may occur during standard therapies, as well as providing capabilities to reinforce typical areas of weakness in an ASD persons social repertoire, such as posture mimicry and eye contact. A goal of this thesis is to show the methodology behind arriving at these design goals so that future designers may follow and improve upon them. Nyku\u27s hardware and software design requirements draw from this foundation. Using this needs first design methodology allows for informed design such that the final product is actually useful to the ASD population. In this work, the information collected is used to design the mechanical components of Nyku. These elements consist of Nyku\u27s Body, Neck & Head, and Omni-wheel base. As with all robots, the mechanical needs then spawn electronics requirements, which are, in turn, presented. In order to tie these systems together, the control architecture is coded. Notably, this thesis results in a novel kinematic model of a spherical manipulation system present in the Omni-wheel Base. This solution is then presented in detail, along with the testing conducted to ensure the model\u27s accuracy. To complete the thesis, overall progress on Nyku is highlighted alongside suggestions for a continuation of the work. Here, the engineering work is compared against the design goals which it tries to fulfill in an effort to ensure that the work has stayed on track. In continuation, this examination maps out future steps needed to optimize the engineering work on Nyku for reliable performance during therapeutic sessions. Finally, a therapeutic plan is proposed given the hardware capabilities of Nyku and the needs of ASD children against the background of modern therapeutic methods

MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics

El libro de actas recoge las aportaciones de los autores a través de los correspondientes artículos a la Dinámica de Sistemas Multicuerpo y la Mecatrónica (Musme). Estas disciplinas se han convertido en una importante herramienta para diseñar máquinas, analizar prototipos virtuales y realizar análisis CAD sobre complejos sistemas mecánicos articulados multicuerpo. La dinámica de sistemas multicuerpo comprende un gran número de aspectos que incluyen la mecánica, dinámica estructural, matemáticas aplicadas, métodos de control, ciencia de los ordenadores y mecatrónica. Los artículos recogidos en el libro de actas están relacionados con alguno de los siguientes tópicos del congreso: Análisis y síntesis de mecanismos ; Diseño de algoritmos para sistemas mecatrónicos ; Procedimientos de simulación y resultados ; Prototipos y rendimiento ; Robots y micromáquinas ; Validaciones experimentales ; Teoría de simulación mecatrónica ; Sistemas mecatrónicos ; Control de sistemas mecatrónicosUniversitat Politècnica de València (2011). MUSME 2011 4 th International Symposium on Multibody Systems and Mechatronics. Editorial Universitat Politècnica de València. http://hdl.handle.net/10251/13224Archivo delegad

Modeling and Control of a Flexible Space Robot to Capture a Tumbling Debris

RÉSUMÉ La conquête spatiale des 60 dernières années a généré une grande quantité d’objets à la dérive sur les orbites terrestres. Leur nombre grandissant constitue un danger omniprésent pour l’exploitation des satellites, et requiert aujourd’hui une intervention humaine pour réduire les risques de collision. En effet, l’estimation de leur croissance sur un horizon de 200 ans, connue sous le nom de “syndrôme de Kessler”, montre que l’accès à l’Espace sera grandement menacé si aucune mesure n’est prise pour endiguer cette prolifération. Le scientifique J.-C. Liou de la National Aeronautics and Space Administration (NASA) a montré que la tendance actuelle pourrait être stabilisée, voire inversée, si au moins cinq débris massifs étaient désorbités par an, tels que des satellites en fin de vie ou des étages supérieurs de lanceur. Parmi les nombreux concepts proposés pour cette mission, la robotique s’est imposée comme une des solutions les plus prometteuses grâce aux retours d’expérience des 30 dernières années. La Station Spatiale Internationale (ISS) possède déjà plusieurs bras robotiques opérationnels, et de nombreuses missions ont démontré le potentiel d’un tel système embarqué sur un satellite. Pour deux d’entre elles, des étapes fondamentales ont été validées pour le service en orbite,et s’avèrent être similaires aux problématiques de la désorbitation des débris. Cette thèse se concentre sur l’étape de capture d’un débris en rotation par un bras robotique ayant des segments flexibles. Cette phase comprend la planification de trajectoire et le contrôle du robot spatial, afin de saisir le point cible du débris de la façon la plus délicate possible. La validation des technologies nécessaires à un tel projet est quasiment impossible sur Terre, et requiert des moyens démesurés pour effectuer des essais en orbite. Par conséquent, la modélisation et la simulation de systèmes multi-corps flexibles est traitée en détails, et constitue une forte contribution de la thèse. À l’aide de ces modèles, une validation mixte est proposée par des essais expérimentaux, en reproduisant la cinématique en orbite par des manipulateurs industriels contrôlés par une simulation en temps réel. En résumé, cette thèse est construite autour des trois domaines suivants : la modélisation des robots spatiaux, le design de lois de contrôle, et leur validation sur un cas test. Dans un premier temps, la modélisation de robots spatiaux en condition d’apesanteur est développée pour une forme “en étoile”.----------ABSTRACT After 60 years of intensive satellite launches, the number of drifting objects in Earth orbits is reaching a shifting point, where human intervention is becoming necessary to reduce the threat of collision. Indeed, a 200 year forecast, known as the “Kessler syndrome”, states that space access will be greatly compromised if nothing is done to address the proliferation of these debris. Scientist J.-C. Liou from the National Aeronautics and Space Administration (NASA) has shown that the current trend could be reversed if at least five massive objects, such as dead satellites or rocket upper stages, were de-orbited each year. Among the various technical concepts considered for debris removal, robotics has emerged, over the last 30 years, as one of the most promising solutions. The International Space Station (ISS) already possesses fully operational robotic arms, and other missions have explored the potential of a manipulator embedded onto a satellite. During two of the latter, key capabilities have been demonstrated for on-orbit servicing, and prove to be equally useful for the purpose of debris removal. This thesis focuses on the close range capture of a tumbling debris by a robotic arm with light-weight flexible segments. This phase includes the motion planning and the control of a space robot, in order to smoothly catch a target point on the debris. The validation of such technologies is almost impossible on Earth and leads to prohibitive costs when performed on orbit. Therefore, the modeling and simulation of flexible multi-body systems has been investigated thoroughly, and is likewise a strong contribution of the thesis. Based on these models, an experimental validation is proposed by reproducing the on-orbit kinematics on a test bench made up of two industrial manipulators and driven by a real-time dynamic simulation. In a nutshell, the thesis is built around three main parts: the modeling of a space robot, the design of control laws, and their validation on a test case. The first part is dedicated to the flexible modeling of a space robot in conditions of weightlessness. A “star-shaped” multi-body system is considered, meaning that the rigid base carries various flexible appendages and robotic arms, assumed to be open mechanical chains only. The classic Newton-Euler and Lagrangian algorithms are brought together to account for the flexibility and to compute the dynamics in a numerically efficient way. The modeling step starts with the rigid fixed-base manipulators in order to introduce the notations, then, détails the flexible ones, and ends with the moving-base system to represent the space robots